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of 191
pro vyhledávání: '"Huang, Jingjia"'
Extremely large-scale multiple-input multiple-output (XL-MIMO) is regarded as one of the key techniques to enhance the performance of future wireless communications. Different from regular MIMO, the XL-MIMO shifts part of the communication region fro
Externí odkaz:
http://arxiv.org/abs/2410.11736
Autor:
Zhang, Yabo, Wang, Zihao, Liew, Jun Hao, Huang, Jingjia, Zhu, Manyu, Feng, Jiashi, Zuo, Wangmeng
In this work, we investigate performing semantic segmentation solely through the training on image-sentence pairs. Due to the lack of dense annotations, existing text-supervised methods can only learn to group an image into semantic regions via pixel
Externí odkaz:
http://arxiv.org/abs/2304.01114
Image-text pretrained models, e.g., CLIP, have shown impressive general multi-modal knowledge learned from large-scale image-text data pairs, thus attracting increasing attention for their potential to improve visual representation learning in the vi
Externí odkaz:
http://arxiv.org/abs/2301.11116
Video-Language Pre-training models have recently significantly improved various multi-modal downstream tasks. Previous dominant works mainly adopt contrastive learning to achieve global feature alignment across modalities. However, the local associat
Externí odkaz:
http://arxiv.org/abs/2301.07463
Semi-supervised learning based methods are current SOTA solutions to the noisy-label learning problem, which rely on learning an unsupervised label cleaner first to divide the training samples into a labeled set for clean data and an unlabeled set fo
Externí odkaz:
http://arxiv.org/abs/2212.10766
Autor:
Huang, Jingjia, Yang, Baixiang
Human Object Interaction (HOI) detection is a challenging task that requires to distinguish the interaction between a human-object pair. Attention based relation parsing is a popular and effective strategy utilized in HOI. However, current methods ex
Externí odkaz:
http://arxiv.org/abs/2207.07979
Building a universal Video-Language model for solving various video understanding tasks (\emph{e.g.}, text-video retrieval, video question answering) is an open challenge to the machine learning field. Towards this goal, most recent works build the m
Externí odkaz:
http://arxiv.org/abs/2207.07885
In recent years, memory-augmented neural networks(MANNs) have shown promising power to enhance the memory ability of neural networks for sequential processing tasks. However, previous MANNs suffer from complex memory addressing mechanism, making them
Externí odkaz:
http://arxiv.org/abs/1906.12087
Autor:
Peng Kunjian, Luo Tiao, Li Jijia, Huang Jingjia, Dong Zizeng, Liu Jia, Pi Chaoqiong, Zou Zizeng, Gu Qin, Liu Ousheng, Zhang Jian-Ting, Luo Zhi-Yong
Publikováno v:
Acta Biochimica et Biophysica Sinica, Vol 54, Pp 647-656 (2022)
Ginsenoside Rh2 is one of rare panaxidiols extracted from Panax ginseng and a potential estrogen receptor ligand that exhibits moderate estrogenic activity. However, the effect of Rh2 on growth inhibition and its underlying molecular mechanism in hum
Externí odkaz:
https://doaj.org/article/feb6cdcb11ea49d89c74f23d1b34b97d
Existing action detection algorithms usually generate action proposals through an extensive search over the video at multiple temporal scales, which brings about huge computational overhead and deviates from the human perception procedure. We argue t
Externí odkaz:
http://arxiv.org/abs/1706.07251